EP2430579A2 - Dispositif et procédé de comparaison de signatures moléculaires - Google Patents

Dispositif et procédé de comparaison de signatures moléculaires

Info

Publication number
EP2430579A2
EP2430579A2 EP10722413A EP10722413A EP2430579A2 EP 2430579 A2 EP2430579 A2 EP 2430579A2 EP 10722413 A EP10722413 A EP 10722413A EP 10722413 A EP10722413 A EP 10722413A EP 2430579 A2 EP2430579 A2 EP 2430579A2
Authority
EP
European Patent Office
Prior art keywords
molecular signatures
biological data
genetic information
signature
signatures
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP10722413A
Other languages
German (de)
English (en)
Inventor
Yasser H. Alsafadi
Nilanjana Banerjee
Vinay VARADAN
Angel J. Janevski
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips Electronics NV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips Electronics NV filed Critical Koninklijke Philips Electronics NV
Publication of EP2430579A2 publication Critical patent/EP2430579A2/fr
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references

Definitions

  • This invention pertains in general to the field of bioinformatics. More particularly the invention relates to a method for clinical decision support by comparing multiple molecular signatures. The invention also relates to a device for comparing multiple molecular signatures, a system for clinical decision support, a computer-readable medium and a use for analyzing clinical data.
  • the present invention seeks to mitigate, alleviate or eliminate one or more of the above-identified deficiencies in the art and disadvantages singly or in any combination.
  • This object is achieved by providing a method, a device, a system, a computer- readable medium and a use for clinical decision support, according to the appended independent patent claims.
  • a general idea of the present invention is to correlate genetic information with molecular signatures and rank the molecular signatures.
  • a method comprising the step of obtaining genetic information. Furthermore, the method comprises a step of obtaining primary biological data corresponding to the genetic information from a knowledge database. The genetic information is then ordered according to the primary biological data. The method also comprises the step of obtaining multiple molecular signatures from a signature data repository. The method further comprises obtaining secondary biological data corresponding to each molecular signature from the knowledge database. The method comprises a step of sorting said molecular signatures according to the correspondence of said secondary biological data and said primary biological data, to form a ranking of said molecular signatures. Finally, the method comprises a step of generating an output signal indicative of a clinical decision based on said ordered genetic information and said ranking of the molecular signatures.
  • a device for clinical decision support comprising units configured to perform the steps according to the first aspect of the invention, when said units are operatively connected to each other.
  • a system for clinical decision support comprises a device according to the second aspect of the invention. Furthermore, the system comprises a knowledge database and a signature data repository. The system also comprises a workstation. The device, knowledge database, signature data repository and workstation are operatively connected by a connecting network.
  • a computer-readable medium having embodied thereon a computer program for processing by a computer.
  • the computer program comprises a code segment for performing the method according to the first aspect of the invention.
  • use of the method according to the first aspect, the device according to the second aspect or the system according to the third aspect, for statistical analysis of clinical data is provided.
  • the method, device, system, and computer-readable medium respectively has at least the advantage that it allows clinical decision support based on comparing multiple molecular signatures, wherein at least two of said molecular signatures are different kinds of molecular signatures. This provides enhanced possibilities for drawing conclusions from genetic information.
  • Fig. 1 is a flowchart of a method according to an embodiment
  • Fig. 2 is a dendrogram of ordered genetic information according to an embodiment
  • Fig. 3 is a matrix showing overlaps of the clustered information according to an embodiment
  • Fig. 4 is are thematic clusters according to an embodiment
  • Fig. 5 is an overview of a thematic cluster and a dendrogram according to an embodiment
  • Fig. 6 is another an overview of a thematic cluster and a dendrogram according to an embodiment
  • Fig. 7 is a flowchart of a device according to an embodiment
  • Fig. 8 is a system according to an embodiment.
  • Fig. 9 is a flowchart of a computer-readable medium according to an embodiment.
  • a gene set G of genes is represented by an ID set of N identifiers.
  • the ID set is first aligned against itself in a matrix.
  • the overlap between the identifier sets IDi and IDj of sets Gi and Gj is defined as the absolute similarity according to the formula:
  • Relative similarity RS(i,j) between the two identifier sets i, j is defined as:
  • a method 10 is provided for using gene sets to reflect various biological processes implicated in cancer. This is done through thematic clusters used to describe and compare four breast cancer prognostic signatures. Genetic information in the form of 25 gene sets is obtained in a step 110 from the database MsigDB (http://www.broad.mit.edu/gsea/msigdb/), well known to a person skilled in the art.
  • MsigDB http://www.broad.mit.edu/gsea/msigdb/
  • curated gene sets are used specifically because they are derived by focusing on a relatively narrow set of biological processes compared to a prognostic signature.
  • One group of gene sets are chosen for their relation to a breast cancer-related signature and another group of gene sets are chosen for control purposes, since they are unlikely to capture breast cancer-related processes.
  • the 25 curated gene sets are shown in table 1. Table 1. 25 curated gene sets from MSigDB.
  • a step 130 the primary biological data is used to order the genetic information represented by the 25 gene sets according to table 1.
  • the ordering may result in clusters of primary biological data.
  • the resulting ordered genetic information from the ordering step 130 is shown in a dendrogram according to Fig. 2.
  • Fig. 3 is a matrix showing overlaps of the clustered information, when two clusters are plotted against each other.
  • contiguous bright regions emerge along the diagonal that correspond to the strongest clusters in the dendrograms.
  • thematic clusters are created. Cancer-related, vasculature, and inflammation sets cluster together, which is evident from the structure of the dendrograms as well as the lit- up areas in Fig. 3.
  • the control gene sets have practically no overlap with the cancer-related sets.
  • the thematic clusters are shown more clearly in Fig. 4.
  • multiple molecular signatures are obtained from a signature data repository in a step 140.
  • the signatures are obtained by choosing breast cancer prognosis gene expression signatures, well known to a person skilled in the art such as Veer, Wang, Caldas and Oncotype.
  • Caldas refers to a prognostic signature of 70 genes that are significantly correlated with survival in early stage node-positive and node-negative tumors.
  • the Veer signature is also a 70-gene-expression signature, which predicts the outcome of pre-menopausal, node-negative and node -positive breast cancer patients with more accuracy than conventional prognostic indicators.
  • the Wang signature is a different 76- gene prognostic signature, which predicts outcome for pre-menopausal, node-negative breast cancer patients.
  • Oncotype refers to a 21 -gene-expression signature which predicts recurrence in tamoxifen-treated node -negative breast cancer.
  • Secondary biological data corresponding to each molecular signature is obtained from the knowledge database in a step 150.
  • the signatures are sorted in a step 160 according to the correspondence of said secondary biological data and said primary biological data, to form a ranking of said molecular signatures.
  • Table 2 shows the number of gene ontology (GO) biological process (BP) term identifiers that describe a subset of the gene sets, i.e. the four prognostic signatures. Table 2. Identifier sets describe gene sets
  • Table 3 shows absolute similarity as intersection of identifier sets of gene sets. For example, the intersection of identifiers (GO terms) of gene set CALDAS and gene set apop (apoptosis) is 9.
  • Table 4 shows relative similarity and collective similarity. Relative similarity between gene set CALDAS and gene set apop is 0.1, which is the absolute similarity between CALDAS and apop (9), normalized by the number of identifiers in the gene set CALDAS (90). The collective similarity of gene set Caldas to the 10 column header gene sets is the row of values corresponding to CALDAS.
  • Fig. 5 illustrates the relationships shown in table 3 and 4 as sorted molecular signatures in relation to the gene sets. A pattern of overlaps between the four signatures (Veer, Wang, Caldas and Oncotype) and the cancer -related gene sets is shown. Additionally, there are no overlaps between the signatures and the control gene sets.
  • the molecular signatures may be ranked.
  • the C-CANCER thematic cluster, which consists of the gene sets: breast cancer estrogen signaling (bees), tumor suppressor (tsup), P53 pathway (p53), and pros-tate cancer- related (pros)
  • breast cancer estrogen signaling bees
  • tumor suppressor tsup
  • P53 pathway p53
  • pros-tate cancer- related pros
  • the overlaps amongst the Oncotype signature and the gene sets are mainly associated with processes such as apoptosis and programmed cell death, whereas the Caldas signature overlaps processes involved in cell cycle and cellular response to starvation and nutrient levels. Similarly, the Veer signature overlaps underline cell growth. In this way, the clusters of molecular signatures may be ranked based on what kind of information is needed.
  • an output signal is generated in a step 170 based on said ordered genetic information and said ranking of the molecular signatures.
  • the output signal may be sent to a decision support workstation.
  • said output signal may be a heat map.
  • the output signal may be a dendrogram.
  • the molecular signatures may be chosen from any source of molecular signatures known within the art, such as nucleotide sequence information, genetic variation information, methylation status information, or expression information.
  • the molecular signature data may be any kind of molecular signature data known within the art, singly or in combination.
  • the primary biological data may be any kind of biological data known within the art, such as biological annotations, genomic annotations, gene ontology, molecular signatures, or specialized gene sets.
  • the biological data may be any kind of biological data known within the art, singly or in combination.
  • molecular signature information singly or in combination
  • primary biological data singly or in combination
  • a device 70 for clinical decision support based on comparison of multiple molecular signatures comprises a first unit 710 configured to obtain genetic information. Furthermore, the device 70 comprises a second unit 720 configured to obtain primary biological data corresponding to the genetic information from a knowledge database. The device 70 also comprises a third unit 730 configured to order said genetic information according to the primary biological data. Also, the device 70 comprises a fourth unit 740 configured to obtain multiple molecular signatures from a signature data repository. The device 70 comprises a fifth unit 750 configured to obtain secondary biological data corresponding to each molecular signature from the knowledge database.
  • the device 70 comprises a sixth unit 760 configured to sort according to the correspondence of said secondary biological data and said primary biological data, to form a ranking of said molecular signatures
  • the device 70 also comprises a seventh unit 770 configured to generate an output signal indicative of a clinical decision based on said ordered genetic information and said ranking of the molecular signatures.
  • the decision support workstation may be a single workstation, or multiple workstations positioned together or separately.
  • user access may be differentiated between multiple workstations, so that a workstation works only for reporting data and another workstation works only to request information or receive the output signal.
  • the units 710, 720, 730, 740, 750, 760, 770 are operatively connected to each other.
  • the units 710, 720, 730, 740, 750, 760, 770 may be embodied as separate physical entities, connected together. However, the units 710, 720, 730, 740, 750, 760, 770 may also be embodied in a singular physical entity. Any combination of the units 710, 720, 730, 740, 750, 760, 770 may be embodied in different separate or unified physical entities. Said entities may further be combined in any setup, forming a connection between the physical entities.
  • system 100 for clinical decision support comprises a device 70 according to embodiments provided herewith.
  • Said system 100 also comprises a knowledge database 1100, where primary biological data is stored and accessed.
  • said system 100 comprises a signature data repository 1200, where secondary biological data is stored and accessed.
  • the system 100 also comprises a workstation 1300, from which a user may enter information, operate the system 100 or interpret the output signal provided by the system 100.
  • Said device 70, knowledge database 1100, signature data repository 1200 and workstation 1300 are operatively connected by a connecting network 1400.
  • the workstation 1300 may be a single workstation, or multiple workstations positioned together or separately.
  • user access may be differentiated between multiple workstations, so that a workstation works only for reporting data and another workstation works only to request information or receive the output signal.
  • the repository 1200 may comprise data from multiple subjects, such as molecular signature data, scientific reports, test data, such as data from clinical studies, patient data, etc.
  • the knowledge database 1100 may comprise data regarding biological annotations, such as methylation, transcription regulatory information or genetic variation, biological ontology data, such as GO data, molecular signature ontology data etc.
  • the method 10, device 70 or system 100 provides information, such as ordered genetic information or ranking that may assist a physician in reaching a diagnosis or treating a patient.
  • the device 70 or system 100 is connected to a hospital information system (HIS), a laboratory information system (LIS), a clinical department information system, a drug knowledge database, a pharmacy information system etc.
  • HIS hospital information system
  • LIS laboratory information system
  • clinical department information system a drug knowledge database
  • pharmacy information system etc.
  • the method 10, device 70 or system 100 may enable selection of biologically and clinically relevant molecular signatures or comparing new signatures to existing established and validated tests.
  • An additional level of interpretation of molecular diagnostic tests is provided compared to the prior art, based on the multi-valued signatures, such as biomarkers, according to embodiments provided herewith. Further interpretation of diagnostic test results is obtained. This is an advantage compared to the prior art, which only obtains simple indication of the status of the test being performed. This makes it possible to convert results from simple tests into actions, such as what other tests need to be performed. Furthermore, in an embodiment, prior art tests may be applied beyond their original scope.
  • a subject is indicated for a disease based on one or more tests, based on signatures discovered in studies of different demographics, it may be possible to utilize such less confident signatures with other established signatures for the correct patient demographics. That is, if the subject is of a demographic background entirely different than the demographics of the subjects used in the clinical studies of the prior art test, it may be possible to indirectly assess how close the indicative tests/signatures are to ones relevant for the subject.
  • a physician may want to have an indication regarding the aggressiveness of the disease.
  • the physician orders molecular signature-based tests A, B, C and D to be performed on biopsies from the subject. The results are negative for C, B and D but positive for A.
  • the physician then performs an analysis according to the method 10 and finds that tests C, B and D are grouped together and have the same underlying biology. Further research regarding the study behind test A, using the device 70 or the system 100, shows that the subject population is based solely on a northern European population. The subject is Chinese, whereby the physician concludes that difference in ethnicity might be the reason behind the conflicting result. The physician thus decides to order tests E and F to confirm the pathobiology of the disease and eventually selects therapy X and Y - specific to the presentation of the disease in the subject.
  • the units 710, 720, 730, 740, 750, 760, 770 may be any units normally used for performing the involved tasks, e.g. a hardware, such as a processor with a memory.
  • the device 70 or the system 100 is comprised in a medical workstation or medical system, such as a Computed Tomography (CT) system, Magnetic Resonance Imaging (MRI) System or Ultrasound Imaging (US) system.
  • CT Computed Tomography
  • MRI Magnetic Resonance Imaging
  • US Ultrasound Imaging
  • a computer-readable medium has embodied thereon a computer program 200 for processing by a computer.
  • the computer program 200 comprises a first code segment 2100 for obtaining genetic information.
  • the computer program 200 further comprises a second code segment 2200 for obtaining primary biological data corresponding to the genetic information from a knowledge database.
  • the computer program 200 also comprises a third code segment 2300 for ordering said genetic information according to the primary biological data.
  • the computer program 200 comprises a fourth code segment 2400 for obtaining multiple molecular signatures from a signature data repository.
  • the computer program 200 also comprises a fifth code 2500 segment for obtaining secondary biological data corresponding to each molecular signature from the knowledge database.
  • the computer program 200 comprises a sixth code segment 2600 for sorting said molecular signatures according to the correspondence of said secondary biological data and said primary biological data, to form a ranking of said molecular signatures.
  • the computer program 200 also comprises a seventh code segment 2700 for generating an output signal indicative of a clinical decision based on said ordered genetic information and said ranking of the molecular signatures.
  • the invention may be implemented in any suitable form including hardware, software, firmware or any combination of these. However, preferably, the invention is implemented as computer software running on one or more data processors and/or digital signal processors.
  • the elements and components of an embodiment of the invention may be physically, functionally and logically implemented in any suitable way. Indeed, the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the invention may be implemented in a single unit, or may be physically and functionally distributed between different units and processors.

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Abstract
EP10722413A 2009-05-11 2010-05-05 Dispositif et procédé de comparaison de signatures moléculaires Ceased EP2430579A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US17698909P 2009-05-11 2009-05-11
PCT/IB2010/051969 WO2010131162A2 (fr) 2009-05-11 2010-05-05 Dispositif et procédé de comparaison de signatures moléculaires

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EP2430579A2 true EP2430579A2 (fr) 2012-03-21

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US (1) US8924232B2 (fr)
EP (1) EP2430579A2 (fr)
CN (1) CN102422294B (fr)
WO (1) WO2010131162A2 (fr)

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Publication number Publication date
US8924232B2 (en) 2014-12-30
CN102422294B (zh) 2015-11-25
CN102422294A (zh) 2012-04-18
WO2010131162A2 (fr) 2010-11-18
US20120109678A1 (en) 2012-05-03
WO2010131162A9 (fr) 2011-01-20

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